text: #
  # Copyright (C) 2018 The Android Open Source Project
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #      http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  #
  
  def test(input0, output0, axes, keep_dims, input_data, output_data):
    model = Model().Operation("REDUCE_MIN", input0, axes, keep_dims).To(output0)
    quant8 = DataTypeConverter().Identify({
        input0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
        output0: ["TENSOR_QUANT8_ASYMM", 0.5, 127],
    })
    Example({
        input0: input_data,
        output0: output_data,
    }, model=model).AddVariations("relaxed", "float16", quant8)
  
  test(
      input0=Input("input0", "TENSOR_FLOAT32", "{3, 2}"),
      input_data=[-1, -2,
                  3, 4,
                  5, -6],
      axes=[-1],
      keep_dims=False,
      output0=Output("output0", "TENSOR_FLOAT32", "{3}"),
      output_data=[-2, 3, -6],
  )
  
  # Tests below were adapted from tensorflow/lite/kernels/reduce_test.cc
  
  test(
      input0=Input("input0", "TENSOR_FLOAT32", "{1}"),
      input_data=[9.527],
      axes=[0],
      keep_dims=True,
      output0=Output("output0", "TENSOR_FLOAT32", "{1}"),
      output_data=[9.527],
  )
  
  test(
      input0=Input("input0", "TENSOR_FLOAT32", "{4, 3, 2}"),
      input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
                  0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6,
                  1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.3, 2.4],
      axes=[1, 0, -3, -3],
      keep_dims=False,
      output0=Output("output0", "TENSOR_FLOAT32", "{2}"),
      output_data=[0.1, 0.2],
  )
  
  test(
      input0=Input("input0", "TENSOR_FLOAT32", "{4, 3, 2}"),
      input_data=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8,
                  0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6,
                  1.7, 1.8, 1.9, 2.0, 2.1, 2.2, 2.3, 2.4],
      axes=[0, 2],
      keep_dims=True,
      output0=Output("output0", "TENSOR_FLOAT32", "{1, 3, 1}"),
      output_data=[0.1, 0.3, 0.5],
  )
  